AI-Modelling and Process

About the Book: The book delves into the fascinating world of Deep Neural Networks (DNNs) a powerful tool within Artificial Intelligence (AI). It explores how DNNs learn and make predictions based on data. Clarifying DNNs: The book explains the core concepts of DNNs their structure and how they extract patterns from training data. Data preparation: Understanding the importance of various datasets including training testing and unseen data in building robust AI models. Machine Learning and Deep Learning: The book provides a clear overview of Machine Learning (ML) and Deep Learning (DL) as foundational concepts for AI development. Python libraries: Learn about Python libraries commonly used for AI and DNN implementation. Designing AI Management Dashboards: Discover how to create dashboards to visualize and monitor AI performance. Real-world applications of AI: Explore the diverse domains where AI is making a significant impact including finance and healthcare. AI Engine integration: Understand the benefits of integrating AI engines with existing systems like ERP. Generative AI: Learn about this exciting subfield of AI focused on creating new data. 50+ video tutorials: The book's website offers video tutorials demonstrating AI forecasting in various domains. Overall AI-Modelling and Process provides a valuable roadmap for understanding and implementing AI in today's data-driven world.